Gramene: development and integration of trait and gene ontologies for rice

Gramene (http://www.gramene.org/) is a comparative genome database for cereal crops and a community resource for rice. We are populating and curating Gramene with annotated rice (Oryza sativa) genomic sequence data and associated biological information including molecular markers, mutants, phenotypes, polymorphisms and Quantitative Trait Loci (QTL). In order to support queries across various data sets as well as across external databases, Gramene will employ three related controlled vocabularies. The specific goal of Gramene is, first to provide a Trait Ontology (TO) that can be used across the cereal crops to facilitate phenotypic comparisons both within and between the genera. Second, a vocabulary for plant anatomy terms, the Plant Ontology (PO) will facilitate the curation of morphological and anatomical feature information with respect to expression, localization of genes and gene products and the affected plant parts in a phenotype. The TO and PO are both in the early stages of development in collaboration with the International Rice Research Institute, TAIR and MaizeDB as part of the Plant Ontology Consortium. Finally, as part of another consortium comprising macromolecular databases from other model organisms, the Gene Ontology Consortium, we are annotating the confirmed and predicted protein entries from rice using both electronic and manual curation.     

Gramene: a resource for comparative grass genomics

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice. Rice, in addition to being an economically important crop, is also a model monocot for understanding other agronomically important grass genomes. Gramene replaces the existing AceDB database ‘RiceGenes’ with a relational database based on Oracle. Gramene provides curated and integrative information about maps, sequence, genes, genetic markers, mutants, QTLs, controlled vocabularies and publications. Its aims are to use the rice genetic, physical and sequence maps as fundamental organizing units, to provide a common denominator for moving from one crop grass to another and is to serve as a portal for interconnecting with other web-based crop grass resources. This paper describes the initial steps we have taken towards realizing these goals.     

MOsDB: an integrated information resource for rice genomics

The MIPS Rice (Oryza sativa) database (MOsDB; http://mips.gsf.de/proj/rice) provides a comprehensive data collection dedicated to the genome information of rice. Rice (O. sativa L.) is one of the most important food crops for over half the world's population and serves as a major model system in cereal genome research. MOsDB integrates data from two publicly available rice genomic sequences, O. sativa L. ssp. indica and O. sativa L. ssp. japonica. Besides regularly updated rice genome sequence information, MOsDB provides an integrated resource for associated analysis data, e.g. internal and external annotation information as well as a complex characterization of all annotated rice genes. The MOsDB web interface supports various search options and allows browsing the database content. MOsDB is continuously expanding to include an increasing range of data type and the growing amount of information on the rice genome.     

Comparative DNA sequence analysis of mapped wheat ESTs reveals the complexity of genome relationships between rice and wheat

The use of DNA sequence-based comparative genomics for evolutionary studies and for transferring information from model species to related large-genome species has revolutionized molecular genetics and breeding strategies for improving those crops. Comparative sequence analysis methods can be used to cross-reference genes between species maps, enhance the resolution of comparative maps, study patterns of gene evolution, identify conserved regions of the genomes, and facilitate interspecies gene cloning. In this study, 5,780 Triticeae ESTs that have been physically mapped using wheat (Triticum aestivum L.) deletion lines and segregating populations were compared using NCBI BLASTN to the first draft of the public rice (Oryza sativa L.) genome sequence data from 3,280 ordered BAC/PAC clones. A rice genome view of the homoeologous wheat genome locations based on sequence analysis shows general similarity to the previously published comparative maps based on Southern analysis of RFLP. For most rice chromosomes there is a preponderance of wheat genes from one or two wheat chromosomes. The physical locations of non-conserved regions were not consistent across rice chromosomes. Some wheat ESTs with multiple wheat genome locations are associated with the non-conserved regions of similarity between rice and wheat. The inverse view, showing the relationship between the wheat deletion map and rice genomic sequence, revealed the breakdown of gene content and order at the resolution conferred by the physical chromosome deletions in the wheat genome. An average of 35% of the putative single copy genes that were mapped to the most conserved bins matched rice chromosomes other than the one that was most similar. This suggests that there has been an abundance of rearrangements, insertions, deletions, and duplications eroding the wheat-rice genome relationship that may complicate the use of rice as a model for cross-species transfer of information in non-conserved regions.     

Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages

The Plant Ontology Consortium (POC) (www.plantontology.org) is a collaborative effort among several plant databases and experts in plant systematics, botany and genomics. A primary goal of the POC is to develop simple yet robust and extensible controlled vocabularies that accurately reflect the biology of plant structures and developmental stages. These provide a network of vocabularies linked by relationships (ontology) to facilitate queries that cut across datasets within a database or between multiple databases. The current version of the ontology integrates diverse vocabularies used to describe Arabidopsis, maize and rice (Oryza sp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500 gene annotations from three species-specific databases, The Arabidopsis Information Resource (TAIR) for Arabidopsis, Gramene for rice and MaizeGDB for maize, can now be queried and retrieved.     

Biological ontologies in rice databases. An introduction to the activities in Gramene and Oryzabase

An enormous amount of information and materials in the field of biology has been accumulating, such as nucleotide and amino acid sequences, gene and protein functions, mutants and their phenotypes, and literature references, produced by the rapid development in this field. Effective use of the information may strongly promote biological studies, and may lead to many important findings. It is, however, time-consuming and laborious for individual researchers to collect information from individual original sites and to rearrange it for their own purpose. A concept, ontology, has been introduced in biology to support and encourage researchers to share and reuse information among biological databases. Ontology has a glossary, named dynamic controlled vocabulary, in which relationships between terms are defined. Since each term is strictly defined and identified with an ID number, a set of data represented in biological ontology is easily accessible to automated information processing, even if the data sets are across several databases and/or different organisms. In this mini-review, we introduce activities in Gramene and Oryzabase, which provide biological ontologies for Oryza sativa (rice).     

The rice kinase database. A phylogenomic database for the rice kinome

The rice (Oryza sativa) genome contains 1,429 protein kinases, the vast majority of which have unknown functions. We created a phylogenomic database (http://rkd.ucdavis.edu) to facilitate functional analysis of this large gene family. Sequence and genomic data, including gene expression data and protein-protein interaction maps, can be displayed for each selected kinase in the context of a phylogenetic tree allowing for comparative analysis both within and between large kinase subfamilies. Interaction maps are easily accessed through links and displayed using Cytoscape, an open source software platform. Chromosomal distribution of all rice kinases can also be explored via an interactive interface.     

The TIGR rice genome annotation resource: annotating the rice genome and creating resources for plant biologists

Rice is not only a major food staple for the world's population but it also is a model species for a major group of flowering plants, the monocotyledonous plants. Draft genomic sequence of two subspecies of rice, Oryza sativa spp. japonica and indica ssp. are publicly available. To provide the community with a resource to data-mine the rice genome, we have constructed an annotation resource for rice (http://www.tigr.org/tdb/e2k1/osa1/). In this resource, we have annotated the rice genome for gene content, identified motifs/domains within the predicted genes, constructed a rice repeat database, identified related sequences in other plant species, and identified syntenic sequences between rice and maize. All of the data is available through web-based interfaces, FTP downloads, and a Distributed Annotation System.     

A universal core genetic map for rice

To facilitate the creation of easily comparable, low-resolution genetic maps with evenly distributed markers in rice (Oryza sativa L.), we conceived of and developed a Universal Core Genetic Map (UCGM). With this aim, we derived a set of 165 anchors, representing clusters of three microsatellite or simple sequence repeat (SSR) markers arranged into non-recombining groups. Each anchor consists of at least three, closely linked SSRs, located within a distance below the genetic resolution provided by common, segregating populations (<500 individuals). We chose anchors that were evenly distributed across the rice chromosomes, with spacing between 2 and 3.5 Mbp (except in the telomeric regions, where spacing was 1.5 Mbp). Anchor selection was performed using in silico tools and data: the O. sativa cv. Nipponbare rice genome sequence, the CHARM tool, information from the Gramene database and the OrygenesDB database. Sixteen AA-genome accessions of the Oryza genus were used to evaluate polymorphisms for the selected markers, including accessions from O. sativa, O. glaberrima, O. barthii, O. rufipogon, O. glumaepatula and O. meridionalis. High levels of polymorphism were found for the tested O. sativa × O. glaberrima or O. sativa × wild rice combinations. We developed Paddy Map, a simple database that is helpful in selecting optimal sets of polymorphic SSRs for any cross that involves the previously mentioned species. Validation of the UCGM was done by using it to develop three interspecific genetic maps and by comparing genetic SSR locations with their physical positions on the rice pseudomolecules. In this study, we demonstrate that the UCGM is a useful tool for the rice genetics and breeding community, especially in strategies based on interspecific hybridisation.     

Introducing GeneDB: a generic database

GeneDB (http://www.genedb.org) is a generic database designed to house annotated and curated sequencing data for small genomes, together with a comprehensive array of genomic and proteomic information, collated from publicly available sources. This first release is a prototype designed with input from the research community and is still under continual development. At present, data from Leishmania major and Trypanosoma brucei are integrated into GeneDB. This user-friendly database will add significantly to the valuable resources already available to the research community via the web.     

A new resource for cereal genomics: 22K barley GeneChip comes of age

In recent years, access to complete genomic sequences, coupled with rapidly accumulating data related to RNA and protein expression patterns, has made it possible to determine comprehensively how genes contribute to complex phenotypes. However, for major crop plants, publicly available, standard platforms for parallel expression analysis have been limited. We report the conception and design of the new publicly available, 22K Barley1 GeneChip probe array, a model for plants without a fully sequenced genome. Array content was derived from worldwide contribution of 350,000 high-quality ESTs from 84 cDNA libraries, in addition to 1,145 barley (Hordeum vulgare) gene sequences from the National Center for Biotechnology Information nonredundant database. Conserved sequences expressed in seedlings of wheat (Triticum aestivum), oat (Avena strigosa), rice (Oryza sativa), sorghum (Sorghum bicolor), and maize (Zea mays) were identified that will be valuable in the design of arrays across grasses. To enhance the usability of the data, BarleyBase, a MIAME-compliant, MySQL relational database, serves as a public repository for raw and normalized expression data from the Barley1 GeneChip probe array. Interconnecting links with PlantGDB and Gramene allow BarleyBase users to perform gene predictions using the 21,439 non-redundant Barley1 exemplar sequences or cross-species comparison at the genome level, respectively. We expect that this first generation array will accelerate hypothesis generation and gene discovery in disease defense pathways, responses to abiotic stresses, development, and evolutionary diversity in monocot plants.     

The institute for genomic research Osa1 rice genome annotation database

We have developed a rice (Oryza sativa) genome annotation database (Osa1) that provides structural and functional annotation for this emerging model species. Using the sequence of O. sativa subsp. japonica cv Nipponbare from the International Rice Genome Sequencing Project, pseudomolecules, or virtual contigs, of the 12 rice chromosomes were constructed. Our most recent release, version 3, represents our third build of the pseudomolecules and is composed of 98% finished sequence. Genes were identified using a series of computational methods developed for Arabidopsis (Arabidopsis thaliana) that were modified for use with the rice genome. In release 3 of our annotation, we identified 57,915 genes, of which 14,196 are related to transposable elements. Of these 43,719 non-transposable element-related genes, 18,545 (42.4%) were annotated with a putative function, 5,777 (13.2%) were annotated as encoding an expressed protein with no known function, and the remaining 19,397 (44.4%) were annotated as encoding a hypothetical protein. Multiple splice forms (5,873) were detected for 2,538 genes, resulting in a total of 61,250 gene models in the rice genome. We incorporated experimental evidence into 18,252 gene models to improve the quality of the structural annotation. A series of functional data types has been annotated for the rice genome that includes alignment with genetic markers, assignment of gene ontologies, identification of flanking sequence tags, alignment with homologs from related species, and syntenic mapping with other cereal species. All structural and functional annotation data are available through interactive search and display windows as well as through download of flat files. To integrate the data with other genome projects, the annotation data are available through a Distributed Annotation System and a Genome Browser. All data can be obtained through the project Web pages at http://rice.tigr.org.     

GrainGenes 2.0. an improved resource for the small-grains community

GrainGenes (http://wheat.pw.usda.gov) is an international database for genetic and genomic information about Triticeae species (wheat [Triticum aestivum], barley [Hordeum vulgare], rye [Secale cereale], and their wild relatives) and oat (Avena sativa) and its wild relatives. A major strength of the GrainGenes project is the interaction of the curators with database users in the research community, placing GrainGenes as both a data repository and information hub. The primary intensively curated data classes are genetic and physical maps, probes used for mapping, classical genes, quantitative trait loci, and contact information for Triticeae and oat scientists. Curation of these classes involves important contributions from the GrainGenes community, both as primary data sources and reviewers of published data. Other partially automated data classes include literature references, sequences, and links to other databases. Beyond the GrainGenes database per se, the Web site incorporates other more specific databases, informational topics, and downloadable files. For example, unique BLAST datasets of sequences applicable to Triticeae research include mapped wheat expressed sequence tags, expressed sequence tag-derived simple sequence repeats, and repetitive sequences. In 2004, the GrainGenes project migrated from the AceDB database and separate Web site to an integrated relational database and Internet resource, a major step forward in database delivery. The process of this migration and its impacts on database curation and maintenance are described, and a perspective on how a genomic database can expedite research and crop improvement is provided.     

A comprehensive radiation hybrid map of the bovine genome comprising 5593 loci

A bovine whole genome 7000-rad radiation hybrid (RH) panel, SUNbRH(7000-rad), was constructed to build a high-resolution RH map. The Shirakawa-USDA linkage map served as a scaffold to construct a framework map of 3216 microsatellites on which 2377 ESTs were ordered. The resulting RH map provided essentially complete coverage across the genome, with 1 cR7000 corresponding to 114 kb, and a cattle-human comparative map of 1716 bovine genes and sequences annotated in the human genome, which covered 79 and 72% of the bovine and human genomes, respectively. We then integrated the bovine RH and comparative maps with BAC fingerprint information in to construct a detailed, BAC-based physical map covering a reported 40-cM quantitative trait locus region for intramuscular fat or "marbling" on BTA 4. In summary, the new, high-resolution SUNbRH7000-rad, comparative, Shirakawa-USDA linkage, and BAC fingerprint maps provide a set of genomic tools for fine mapping regions of interest in cattle.     

The Burkholderia Genome Database: facilitating flexible queries and comparative analyses

As the genome sequences of multiple strains of a given bacterial species are obtained, more generalized bacterial genome databases may be complemented by databases that are focused on providing more information geared for a distinct bacterial phylogenetic group and its associated research community. The Burkholderia Genome Database represents a model for such a database, providing a powerful, user-friendly search and comparative analysis interface that contains features not found in other genome databases. It contains continually updated, curated and tracked information about Burkholderia cepacia complex genome annotations, plus other Burkholderia species genomes for comparison, providing a high-quality resource for its targeted cystic fibrosis research community. AVAILABILITY: http://www.burkholderia.com. Source code: GNU GPL.